Pub Date : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670741
S. Santhosh Baboo, S. Sasikala
This paper deals with the advanced and developed methodology know for cancer multi classification using an Extreme Learning Machine (ELM) for microarray gene expression cancer diagnosis, this used for directing multicategory classification problems in the cancer diagnosis area. ELM avoids problems like local minima; improper learning rate and over fitting commonly faced by iterative learning methods and completes the training very fast. We have evaluated the multicategory0 classification performance of ELM on benchmark microarray data sets for cancer diagnosis, namely, the Lymphoma data set. The results indicate that ELM produces comparable or better classification accuracies with reduced training time and implementation complexity compared to artificial neural networks methods like conventional back-propagation ANN, Linder's SANN, and Support Vector Machine.
{"title":"Multicategory classification using an Extreme Learning Machine for microarray gene expression cancer diagnosis","authors":"S. Santhosh Baboo, S. Sasikala","doi":"10.1109/ICCCCT.2010.5670741","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670741","url":null,"abstract":"This paper deals with the advanced and developed methodology know for cancer multi classification using an Extreme Learning Machine (ELM) for microarray gene expression cancer diagnosis, this used for directing multicategory classification problems in the cancer diagnosis area. ELM avoids problems like local minima; improper learning rate and over fitting commonly faced by iterative learning methods and completes the training very fast. We have evaluated the multicategory0 classification performance of ELM on benchmark microarray data sets for cancer diagnosis, namely, the Lymphoma data set. The results indicate that ELM produces comparable or better classification accuracies with reduced training time and implementation complexity compared to artificial neural networks methods like conventional back-propagation ANN, Linder's SANN, and Support Vector Machine.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121960687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670774
B. Muruganatham, M. Sanjith, B. Krishna Kumar, S. S. Satya Murty, P. Swaminathan
A novel method to diagnose the bearing fault is presented. The proposed method is based on the analysis of the bearing vibration signals using Singular Spectrum Analysis (SSA). SSA is a non-parametric technique of time series analysis that decomposes the acquired bearing vibration signals into an additive set of time series to extract information correlated with the condition of the bearing. Information in terms of time-domain features extracted from the SSA processed signal has been presented to a neural network for determination of inner race bearing fault. The result shows the effectiveness of the proposed method.
{"title":"Inner race bearing fault detection using Singular Spectrum Analysis","authors":"B. Muruganatham, M. Sanjith, B. Krishna Kumar, S. S. Satya Murty, P. Swaminathan","doi":"10.1109/ICCCCT.2010.5670774","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670774","url":null,"abstract":"A novel method to diagnose the bearing fault is presented. The proposed method is based on the analysis of the bearing vibration signals using Singular Spectrum Analysis (SSA). SSA is a non-parametric technique of time series analysis that decomposes the acquired bearing vibration signals into an additive set of time series to extract information correlated with the condition of the bearing. Information in terms of time-domain features extracted from the SSA processed signal has been presented to a neural network for determination of inner race bearing fault. The result shows the effectiveness of the proposed method.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130447824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670788
Mahender P, N. S, S. Behera
A Dielectric resonator antenna design is presented for Wireless Local Area Network (WLAN) applications. By using a dielectric resonator with an inverted U-shape cross section and optimized rectangular patch adhered in between the dielectric resonator as a feeding mechanism, an impedance bandwidth of about 15.7% and covering a frequency range of 5.1 to 5.97 GHz is achieved and resonating at 5.5GHz. The proposed antenna is suitable for wireless local area networks (WLAN) applications in 5–6 GHz frequency range. This U Shaped DRA exceeds the bandwidth requirements for the IEEE 802.11a wireless local area network (WLAN) applications (5.15–5.35 GHz and 5.725–5.825 GHz) within a 2∶1 VSWR. Parametric studies of the antennas with CST microwave based design data and simulated results are presented here.
{"title":"Inverted U-shaped Dielectric resonator antenna for WLAN","authors":"Mahender P, N. S, S. Behera","doi":"10.1109/ICCCCT.2010.5670788","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670788","url":null,"abstract":"A Dielectric resonator antenna design is presented for Wireless Local Area Network (WLAN) applications. By using a dielectric resonator with an inverted U-shape cross section and optimized rectangular patch adhered in between the dielectric resonator as a feeding mechanism, an impedance bandwidth of about 15.7% and covering a frequency range of 5.1 to 5.97 GHz is achieved and resonating at 5.5GHz. The proposed antenna is suitable for wireless local area networks (WLAN) applications in 5–6 GHz frequency range. This U Shaped DRA exceeds the bandwidth requirements for the IEEE 802.11a wireless local area network (WLAN) applications (5.15–5.35 GHz and 5.725–5.825 GHz) within a 2∶1 VSWR. Parametric studies of the antennas with CST microwave based design data and simulated results are presented here.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132638126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670734
M. Gopichand, V. Swetha, A. Ananda Rao
Statistical evidence has shown that programmers perform better when following a defined, repeatable process such as the Personal Software Process (PSP).Anecdotal and qualitative evidence from industry indicates that two programmers working side-by-side at one computer, collaborating on the same design, algorithm, code, or test, perform substantially better than the two working alone i.e. pair programming. Bringing these two ideas together, a new Software Process has been formulated. The Hybrid Personal Software Process (HPSP) is a defined, repeatable process for two programmers working collaboratively. The development time and cost of the product are reduced in HPSP when compared with PSP programming.
{"title":"Software defect detection and process improvement using personal software process data","authors":"M. Gopichand, V. Swetha, A. Ananda Rao","doi":"10.1109/ICCCCT.2010.5670734","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670734","url":null,"abstract":"Statistical evidence has shown that programmers perform better when following a defined, repeatable process such as the Personal Software Process (PSP).Anecdotal and qualitative evidence from industry indicates that two programmers working side-by-side at one computer, collaborating on the same design, algorithm, code, or test, perform substantially better than the two working alone i.e. pair programming. Bringing these two ideas together, a new Software Process has been formulated. The Hybrid Personal Software Process (HPSP) is a defined, repeatable process for two programmers working collaboratively. The development time and cost of the product are reduced in HPSP when compared with PSP programming.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132812943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670744
Sandhya Yogi, Prof. K. R. Subhashini, Prof. J. K. Satapathy, Shiv Kumar
One of the main obstacles to reliable communications is the inter symbol interference. An adaptive equalizer is required at the receiver to mitigate the effects of non-ideal channel characteristics and to obtain reliable data transmission. The conventional way to combat with ISI is to include an equalizer in the receiver. This paper presents a new approach to equalization of communication channels using Functional Link Artificial Neural Networks (FLANNs). A novel method of training the FLANNs using PSO Algorithm is described. The performance of the proposed network has been compared with the conventional LMS based channel equalizer and FLANN trained with BP algorithm based equalizer. From the results it can be noted that the proposed algorithm improves the classification capability of the FLANNs in differentiating the received data.
{"title":"Equalization of digital communication channels based on PSO algorithm","authors":"Sandhya Yogi, Prof. K. R. Subhashini, Prof. J. K. Satapathy, Shiv Kumar","doi":"10.1109/ICCCCT.2010.5670744","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670744","url":null,"abstract":"One of the main obstacles to reliable communications is the inter symbol interference. An adaptive equalizer is required at the receiver to mitigate the effects of non-ideal channel characteristics and to obtain reliable data transmission. The conventional way to combat with ISI is to include an equalizer in the receiver. This paper presents a new approach to equalization of communication channels using Functional Link Artificial Neural Networks (FLANNs). A novel method of training the FLANNs using PSO Algorithm is described. The performance of the proposed network has been compared with the conventional LMS based channel equalizer and FLANN trained with BP algorithm based equalizer. From the results it can be noted that the proposed algorithm improves the classification capability of the FLANNs in differentiating the received data.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130784857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670530
C. Vennila Arasu, Puneet Hyanki, H. Lakshman Sharma, G. Lakshminarayanan, M. Lee, S. Ko
Orthogonal frequency division multiplexing (OFDM) signals have a generic problem of high peak to average power ratio (PAPR) which is defined as the ratio of the peak power to the average power of the OFDM signal. The drawback of the high PAPR is that the dynamic range of the power amplifiers (PA) & digital-to-analog (D/A) converters required during the transmission and reception of the signal is higher. As a result, the total cost of the transceiver increases, with reduced efficiency. This paper includes an idea of the PAPR constraint, along with the implementation and analysis of some specific algorithms for PAPR reduction of the OFDM signals. All the PAPR reduction algorithms are implemented and tested in the OFDM transceiver designed using Matlab. Analyzing some specific algorithms, we propose a novel algorithm by combining the subcarrier phase adjustment and linear combination of the time domain OFDM signals. Simulation results for a OFDM system employing Quadrature Amplitude Shift Keying (QASK) symbols and Quadrature Amplitude Modulation (QAM) can achieve a PAPR reduction of 5 dB.
{"title":"PAPR reduction for improving performance of OFDM system","authors":"C. Vennila Arasu, Puneet Hyanki, H. Lakshman Sharma, G. Lakshminarayanan, M. Lee, S. Ko","doi":"10.1109/ICCCCT.2010.5670530","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670530","url":null,"abstract":"Orthogonal frequency division multiplexing (OFDM) signals have a generic problem of high peak to average power ratio (PAPR) which is defined as the ratio of the peak power to the average power of the OFDM signal. The drawback of the high PAPR is that the dynamic range of the power amplifiers (PA) & digital-to-analog (D/A) converters required during the transmission and reception of the signal is higher. As a result, the total cost of the transceiver increases, with reduced efficiency. This paper includes an idea of the PAPR constraint, along with the implementation and analysis of some specific algorithms for PAPR reduction of the OFDM signals. All the PAPR reduction algorithms are implemented and tested in the OFDM transceiver designed using Matlab. Analyzing some specific algorithms, we propose a novel algorithm by combining the subcarrier phase adjustment and linear combination of the time domain OFDM signals. Simulation results for a OFDM system employing Quadrature Amplitude Shift Keying (QASK) symbols and Quadrature Amplitude Modulation (QAM) can achieve a PAPR reduction of 5 dB.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133431082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670743
Suman Patil, Lalita Madanbhavi
“Process Automation in Strategic Command - Decision Support System” (PASC - DSS) is a program being executed by Center for Artificial Intelligence and Robotics (CAIR) to provide Indian Defence with a system built on leading edge technology. PASC - DSS helps in collecting, collating, filtering, processing, synthesizing and displaying the information gathered from various sources and provide support while decision making. The system also helps to provide support for gathering information for various resources of Indian Defence and utilizing this information at the time of executing various operations. This paper first gives the insight into decision support systems. Then we present the system.
{"title":"Web based decision support system for management of defence activities: Process Automation in Strategic Command - Decision Support System (PASC-DSS)","authors":"Suman Patil, Lalita Madanbhavi","doi":"10.1109/ICCCCT.2010.5670743","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670743","url":null,"abstract":"“Process Automation in Strategic Command - Decision Support System” (PASC - DSS) is a program being executed by Center for Artificial Intelligence and Robotics (CAIR) to provide Indian Defence with a system built on leading edge technology. PASC - DSS helps in collecting, collating, filtering, processing, synthesizing and displaying the information gathered from various sources and provide support while decision making. The system also helps to provide support for gathering information for various resources of Indian Defence and utilizing this information at the time of executing various operations. This paper first gives the insight into decision support systems. Then we present the system.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121982969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670722
A. Suresh, S. Rama Reddy
Modelling and simulation of closed loop controlled class D current source resonant inverter (CSRI) for ferromagnetic load is presented in this paper. The converter can operate effectively even for fluctuating source and it operates in zero-current switching mode. The switching devices are connected through a common ground and need only a single DC power supply for the gate driver circuitry. The aim of this work is to develop an induction heater system with minimum hardware. The simulink model of closed loop system is presented. The results of simulation are also presented.
{"title":"Simulation of closed loop controlled current source inverter fed ferromagnetic load","authors":"A. Suresh, S. Rama Reddy","doi":"10.1109/ICCCCT.2010.5670722","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670722","url":null,"abstract":"Modelling and simulation of closed loop controlled class D current source resonant inverter (CSRI) for ferromagnetic load is presented in this paper. The converter can operate effectively even for fluctuating source and it operates in zero-current switching mode. The switching devices are connected through a common ground and need only a single DC power supply for the gate driver circuitry. The aim of this work is to develop an induction heater system with minimum hardware. The simulink model of closed loop system is presented. The results of simulation are also presented.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"47 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126007821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670529
S. A. Joshi, T. Rukmini, H. Mahesh
Multiple Input Multiple Output (MIMO) is a radio communication technology or RF technology that is being mentioned and used in many new technologies these days. The capacity of such a system depends on transmit and receive antenna strategies. The MIMO capacity scales roughly and linearly with the number of Transmitter and Receiver antennas. The two core approaches have been adopted to study the system performance are namely SVD and correlation matrix approach. These methods indicate that the capacity gain obtained from multiple antennas, heavily depends on the amount of channel knowledge at either the receiver or transmitter, the channel SNR, and the correlation between the channel gains on each antenna element. The proposed work explores numerical results of capacity with power allocation in Gaussian, Raleigh fading channels. Simulation of various different transmit and receive antenna strategies like, Independent Rayleigh fading channels in CSI / CDI mode, transmit and receive strategies in Additive White Gaussian Noise (AWGN) environment.
{"title":"System performance analysis of MIMO channel capacity with channel state approaches","authors":"S. A. Joshi, T. Rukmini, H. Mahesh","doi":"10.1109/ICCCCT.2010.5670529","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670529","url":null,"abstract":"Multiple Input Multiple Output (MIMO) is a radio communication technology or RF technology that is being mentioned and used in many new technologies these days. The capacity of such a system depends on transmit and receive antenna strategies. The MIMO capacity scales roughly and linearly with the number of Transmitter and Receiver antennas. The two core approaches have been adopted to study the system performance are namely SVD and correlation matrix approach. These methods indicate that the capacity gain obtained from multiple antennas, heavily depends on the amount of channel knowledge at either the receiver or transmitter, the channel SNR, and the correlation between the channel gains on each antenna element. The proposed work explores numerical results of capacity with power allocation in Gaussian, Raleigh fading channels. Simulation of various different transmit and receive antenna strategies like, Independent Rayleigh fading channels in CSI / CDI mode, transmit and receive strategies in Additive White Gaussian Noise (AWGN) environment.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129312601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670753
U. Mahbub, C. Shahnaz, S. Fattah
This paper deals with the problem of noise cancellation of speech signals in an acoustic environment. In this regard, generally, different adaptive filter algorithms are employed, many of them may lack the flexibility of controlling the convergence rate, range of variation of filter coefficients, and consistency in error within tolerance limit. In order to achieve these desirable attributes as well as to cancel noise effectively, unlike conventional approaches, we formulate the task of noise cancellation as a coefficient optimization problem whereby we introduce and exploit the particle swarm optimization (PSO) algorithm. In this problem, the PSO is designed to perform the error minimization in frequency domain. The outcomes from extensive experimentations show that the proposed PSO based acoustic noise cancellation method provides high performance in terms of SNR improvements with a satisfactory convergence rate in comparison to that obtained by some of the state-of-the-art methods.
{"title":"An adaptive noise cancellation scheme using particle swarm optimization algorithm","authors":"U. Mahbub, C. Shahnaz, S. Fattah","doi":"10.1109/ICCCCT.2010.5670753","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670753","url":null,"abstract":"This paper deals with the problem of noise cancellation of speech signals in an acoustic environment. In this regard, generally, different adaptive filter algorithms are employed, many of them may lack the flexibility of controlling the convergence rate, range of variation of filter coefficients, and consistency in error within tolerance limit. In order to achieve these desirable attributes as well as to cancel noise effectively, unlike conventional approaches, we formulate the task of noise cancellation as a coefficient optimization problem whereby we introduce and exploit the particle swarm optimization (PSO) algorithm. In this problem, the PSO is designed to perform the error minimization in frequency domain. The outcomes from extensive experimentations show that the proposed PSO based acoustic noise cancellation method provides high performance in terms of SNR improvements with a satisfactory convergence rate in comparison to that obtained by some of the state-of-the-art methods.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127157758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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